This paper has presented a study of various image fusion techniques. The main objective of vision fusion is to merging information from multiple images of the same view in order to deliver only the useful information. The principal component averaging (PCA) based methods of vision fusion are more suitable and time-saving in real-time system using PCA based standards of still images. The overall...

Multi-focus portable plenoptic camera devices provide a reasonable tradeoff between spatial and angular resolution while enlarging the depth of field of a standard camera. Many applications using the data captured by these camera devices require or benefit from correspondences established between the single microlens images. In this work we propose a lens-based depth estimation scheme based on ...

Image fusion deals with the integration of multi modal images from various sensors, with visual and infrared, to MMW images, aiming at achieving improved image quality to better support improved image classification, monitoring, surveillance and etc. The main goal of this paper is to introduce a new approach to fuse visual image and infrared images by complex wavelet taking depth of focus into ...

In this paper, a novel image fusion algorithm based on local clarity of spiking cortical model (SCM) is put forward. Firstly, the source images are fused based on local area clarity, and this strategy can keep the focus area of source images. Then, we utilize the SCM to fuse the focus edge of source images. There are five parameters that need to be set in SCM. However, these parameters are hard...

This paper presented a simple and efficient algorithm for multi-focus image fusion, which used a multiresolution signal decomposition scheme called Laplacian pyramid method. The principle of Laplacian pyramid transform is introduced, and based on it the fusion strategy is described in detail. The method mainly composed of three steps. Firstly, the Laplacian pyramids of each source image are dec...

A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum’s algorithm or...

A method for synthesizing enhanced depth of field digital still camera pictures using multiple differently focused images is presented. This technique exploits only spatial image gradients in the initial decision process. The spatial gradient as a focus measure has been shown to be experimentally valid and theoretically sound under weak assumptions with respect to unimodality and monotonicity. ...

It is now widely acknowledged that traditional wavelets are not very effective in dealing with multidimensional signals containing distributed discontinuities. Shearlet Transform is a new discrete multiscale directional representation, which combines the power of multiscale methods with a unique ability to capture the geometry of multidimensional data and is optimally efficient in representing ...

The effective measurement of pixel’s sharpness is a key factor in multi-focus image fusion. In this paper, a gray image is considered as a two-dimensional surface, and the neighbor distance deduced from the oriented distance in differential geometry is used as a measure of pixel’s sharpness, where the smooth image surface is restored by kernel regression. Based on the deduced neighbor distance ...

Work on multiscale issues presents countless challenges that have been long attacked by GIScience researchers. Research is usually concentrated in one of two directions new data models to support handling multiple scales, or data structures and algorithms to process data across scales. Complementary implementation aspects are concerned with generalization (and/or virtualization of distinct scal...